add function docstring

src/demoses_distibuted_optimization/define_consumer_parameters.py

+from typing import Dict
 import pandas as pd
 import pyomo.environ as pyo
-from typing import Dict
 
 
 def define_consumer_parameters(agent: str, model: pyo.AbstractModel, data: Dict, ts: pd.DataFrame) -> pyo.AbstractModel:
+    """Define parmaters common to all consumer agents."""
     # Extract consumer parameter values from data
     total_consumers = data['General']['totConsumers']
     share_of_agent = data['Consumers'][agent]['Share']
@@ -17,7 +18,7 @@ def define_consumer_parameters(agent: str, model: pyo.AbstractModel, data: Dict,
     # Declare consumer optimization parameters (but do not construct yet)
     model.demand_profile = pyo.Param(model.time, name='demand_profile', initialize=dict(enumerate(demand_profile)), mutable=False)
     model.pv_profile = pyo.Param(model.time, name='pv_profile', initialize=dict(enumerate(pv_profile)), mutable=False)
-    
+
     return model